From 4364d780c5ee7fa9b5e3b7e8e1a7d88e86216932 Mon Sep 17 00:00:00 2001
From: Alex Merose <al@merose.com>
Date: Wed, 15 Jan 2025 14:43:00 -0800
Subject: [PATCH] Move private function to the bottom of the file.

---
 cubed/array_api/statistical_functions.py | 54 ++++++++++++------------
 1 file changed, 27 insertions(+), 27 deletions(-)

diff --git a/cubed/array_api/statistical_functions.py b/cubed/array_api/statistical_functions.py
index b26279bc..07b7f231 100644
--- a/cubed/array_api/statistical_functions.py
+++ b/cubed/array_api/statistical_functions.py
@@ -113,33 +113,6 @@ def min(x, /, *, axis=None, keepdims=False, split_every=None):
     )
 
 
-def _validate_and_define_numeric_or_bool_dtype(x, dtype=None, *, fname=None, device=None):
-    """Validate the type of the numeric function. If it's None, provide a good default dtype."""
-    dtypes = __array_namespace_info__().default_dtypes(device=device)
-
-    # Validate.
-    # boolean is allowed by numpy
-    if x.dtype not in _numeric_dtypes and x.dtype not in _boolean_dtypes:
-        errmsg = "Only numeric or boolean dtypes are allowed"
-        if fname:
-           errmsg += f" in {fname}"
-        raise TypeError(errmsg)
-
-    # Choose a good default dtype, when None
-    if dtype is None:
-        if x.dtype in _boolean_dtypes:
-            dtype = dtypes['integral']
-        elif x.dtype in _signed_integer_dtypes:
-            dtype = dtypes['integral']
-        elif x.dtype in _unsigned_integer_dtypes:
-            #TODO(#658): I don't think "indexing" --> uint64; is this correct?
-            dtype = dtypes['indexing']
-        else:
-            dtype = x.dtype
-
-    return dtype
-
-
 def prod(x, /, *, axis=None, dtype=None, keepdims=False, split_every=None, device=None):
     dtype = _validate_and_define_numeric_or_bool_dtype(x, dtype, fname="prod", device=device)
     extra_func_kwargs = dict(dtype=dtype)
@@ -249,3 +222,30 @@ def _var_combine(a, axis=None, correction=None, **kwargs):
 
 def _var_aggregate(a, correction=None, **kwargs):
     return nxp.divide(a["M2"], a["n"] - correction)
+
+
+def _validate_and_define_numeric_or_bool_dtype(x, dtype=None, *, fname=None, device=None):
+    """Validate the type of the numeric function. If it's None, provide a good default dtype."""
+    dtypes = __array_namespace_info__().default_dtypes(device=device)
+
+    # Validate.
+    # boolean is allowed by numpy
+    if x.dtype not in _numeric_dtypes and x.dtype not in _boolean_dtypes:
+        errmsg = "Only numeric or boolean dtypes are allowed"
+        if fname:
+            errmsg += f" in {fname}"
+        raise TypeError(errmsg)
+
+    # Choose a good default dtype, when None
+    if dtype is None:
+        if x.dtype in _boolean_dtypes:
+            dtype = dtypes['integral']
+        elif x.dtype in _signed_integer_dtypes:
+            dtype = dtypes['integral']
+        elif x.dtype in _unsigned_integer_dtypes:
+            #TODO(#658): I don't think "indexing" --> uint64; is this correct?
+            dtype = dtypes['indexing']
+        else:
+            dtype = x.dtype
+
+    return dtype